Factors Influencing the Attrition Rate of a 10-Week Multimodal Rehabilitation Program in Patients After Lung Transplant: A Neural Network Analysis.

Background/objectives: Despite the effectiveness of exercise and nutritional interventions to improve aerobic capacity and quality of life in lung transplant (LT) recipients, their compliance is low. Strategies to reduce the high attrition rate (participants lost over time) is a major challenge. Artificial neural networks (ANN) may assist in the early identification of patients with high risk of attrition.

Unsupervised Cluster Analysis Reveals Distinct Subtypes of ME/CFS Patients Based on Peak Oxygen Consumption and SF-36 Scores.

Purpose: Myalgic encephalomyelitis, commonly referred to as chronic fatigue syndrome (ME/CFS), is a severe, disabling chronic disease and an objective assessment of prognosis is crucial to evaluate the efficacy of future drugs. Attempts are ongoing to find a biomarker to objectively assess the health status of (ME/CFS), patients. This study therefore aims to demonstrate that oxygen consumption is a biomarker of ME/CFS provides a method to classify patients diagnosed with ME/CFS based on their responses to the Short Form-36 (SF-36) questionnaire, which can predict oxygen consumption using cardiopulmonary exercise testing (CPET).

Predictors of respiratory complications in patients with C5-T5 spinal cord injuries.

Study Design: Retrospective chart audit.

Objectives: Describing the respiratory complications and their predictive factors in patients with acute traumatic spinal cord injuries at C5-T5 level during the initial hospitalization.

Setting: Hospital Vall d'Hebron, Barcelona.